A New Semantic Cache Management Method in Mobile Databases

Transcription

1 Journal o Compuer Science 1 (3): , 25 ISSN Science Publicaions, 25 A New Semanic Cache Managemen Mehod in Mobile Daabases Shengei Shi, Jianzhong Li and Chaokun Wang School o Compuer Science and Technology, Harbin Insiue o Technology Harbin 151,People s Republic o China Absrac: In mobile daabase sysems, caching is a crucial way o improve he perormance because a new query can be parially answered locally when he clien is coninuously moving around. Semanic caching has been paid much aenion in radiional daabase sysems. However, he mehods o semanic cache managemen proposed in hose sysems are no suiable or mobile compuing environmen. Moreover, alhough many improved semanic caching sraegies or mobile compuing applicaion have been proposed in recen years, ew papers discussed semanic cache coherence conrol, which is very imporan in mobile compuing environmen. In his paper, we propose some new semanic cache model and managemen algorihms, which can signiicanly reduce he unnecessary uplink requess and downlink broadcass compared o previous schemes. Simulaion experimens are carried ou o evaluae he proposed sraegy. Key words: Semanic cache, coherence managemen, mobile daabases INTRODUCTION Semanic caching has been paid much aenion in radiional daabase sysems. In [3], a semanic model or clien-side caching and replacemen is proposed. Compared wih he radiional caching sraegies, such as page caching and uple caching, semanic caching mainains a semanic descripion o he daa in cache. And a disance uncion called Manhaan disance is proposed o deermine which cache iem o be discarded. In [4], wo issues are discussed. One is called cache compleeness, which deermines wheher a new query can be saisied in is local cache or no, and anoher one is called cache currency, which deals wih he eec on clien caches o updaes commied a he daabase server. In [11], heerogeneous sysems are discussed or semanic cache managemen. In [1], a semanic caching scheme is used o access locaion dependen daa in mobile compuing. The emphases o he paper are pu on modeling he mobiliy o he mobile clien and he LDQ, and he mehod o cache replacemen is proposed. The conribuion o he paper is is FAR algorihm o cache replacemen, which akes he mobiliy o he clien ino consideraion. In [5], a cluser-based approach is proposed o manage semanic cache. Queries are divided semanically ino relaed or adjacen groups, which are called clusers. The cache replacemen mehod, which deals wih he semanic inormaion o clusers, is more eicien han radiional cache replacemen mehods such as LRU ec. And many works such as in [12] also proposed approach o deal wih he problem. Bu up o now, ew papers have discussed semanic cache coherence conrol, which is very imporan in mobile compuing environmen. Alhough many cache invalidaion sraegies or mobile environmens have been proposed such as in [6,7,8,9,13,14,15], hey have 351 nohing o do wih semanic caching. In [1], a novel cache invalidaion repor mehod is proposed and i urns ou o be a semanic-based cache managemen sraegy. In his paper, we will address he problems associaed wih he IR-based semanic cache invalidaion sraegies. Firsly, we propose some new semanic cache model, PR-ree and TS-Cache. Secondly, some cache managemen algorihms which are based on hese model are proposed. Finally, simulaion experimens are carried ou o evaluae he proposed sraegy. Sysem Model Hybrid Predicae Model: Suppose a relaion which consiss o n aribues: A 1, A 2, A n. We divide hese aribues ino wo classes [1]. One is called LDA (Locaion Dependen Aribue), which can be used o ideniy he recangle scope o he resul o a LDQ (Locaion Dependen Query). Anoher class is called NLDA (Non Locaion Dependen Aribue), which is oen used o speciy he iler condiions o a query in a recangle area resriced by LDAs. In our proposed mehod we use he hybrid predicae represenaion. We use muli-aribue hashing uncion on he LDAs o represen he predicae scope. Suppose he LDAs are AX and AY represening he laiude and longiude coordinaes respecively. Oher NLDAs are denoed by A 3, A 4,, A n. Each LDA is hashed ino sring a x and a y by hash uncion H x and H y separaely. Dieren rom previously proposed mehod [1] we use addiional sring a o indicae he exac range value o a LDA in a predicae represenaion. For NLDA, we don hash hem ino a sring bu keep heir original value a i insead. Then, he predicae or a record or a LDQ is denoed by a x a y, a x, a y, a 3,, a n, where is he sring concaenaion operaor. In a predicae, i an aribue is no included, we use characer * o denoe

2 don care condiion jus like in [1]. PR-ree Based Global Predicae Caching Managemen Model a he Server Deiniion 1: PR-ree (Predicae R-ree): PR-ree is a R-ree based index srucure used by he server o index he predicae o LDQ commied by he clien. Lea Node o PR-ree is: LN={(R_LDA, µ, q, J. Compuer Sci., 1 (3): , 25 _ ), las _ updae, las query where R_LDA is he recangle secion speciied by he scope values o LDA in a LDQ, µ and q respecively reer o he updae requency and query requency o area which R_LDA covers, and las _ updae and las _ query are he laes updae and query ime o hashing area covered by R_LDA. Suppose he number o hashing secions covered by R_LDA is k, hen k ( ( ni ui )) µ i 1 = = k, q ni i = 1 k ( ( ni qi )) = i = 1 k ni i = 1 where n i is he number o daa iems in he hashing secion i, and u i and q i are he updae and query requency o hashing secion i respecively. Deiniion 2: PU (Poin Updae Operaion); In he PU operaion, he server only updaes one record. Deiniion 3: RU (Range Updae Operaion); The server updaes a se o records according o a range predicae. Deiniion 4: HP-IR (Hybrid Predicae Invalid Repor) is deined as a uple (HPR, Updae Operaion, TS, [Rid]), where HPR is he hybrid predicae represenaion. Updae_Operaion is PU or RU, TS is he imesamp o updae operaion, and Rid is he record id which is updaed by PU and i is only used when Updae_Operaion is PU. Predicae Caching Managemen Model a he Clien Deiniion 5: HPCD (Hybrid Predicae Cache Descripion) is deined as a se o uple (id, HPR, p-conen, UQ, Ts, Coun_Updae), where id is he ideniier o he PCD iem, HPR is hybrid predicae represenaion o he daa records received rom he server beore, p-conen is he poiner poin o he real daa buer, UQ is a queue o some records o be rerieved rom he server laer; Ts is he imesamp o his PCD; Coun_Updae is he updaing imes o he cache conen. TS-Cache Model Deiniion 6: The probabiliy model o daa is deined as PM odel ::= (A r, L ocaion, TS-M, CR, T samp ). Where A r is he aribue o daa, L ocaion ideniies he locaion o 352 daa, TS-M is ime-series model o daa such as AR or ARMA; CR is conidence region o error bound beween acual value o daa and prediced value rom TS-M wih speciic probabiliy, and T samp is ime samp in which he TS-M is esablished. Deiniion 7: The TS-cache model is deined as TS-Cache::= (Q uery, PM odel ). Where Q uery is he query which ges resuls rom servers. PM odel has been deined above and is used o answer he Q uery. Deiniion 8: Time-Series based Cache Invalid Repor Model (TS-IR) is deined as TS-IR::= (A r, L ocaion, TS-M RawDaa, error, H os B roadcas, T samp ). TS-IR is used o inorm he cliens o change he parameers o PM odel when he error o prediced value exceeds he error bound predeined. A r, L ocaion and TS-M are he same as deined in PM odel. RawDaa is raw daao o daa source. error shows he dierence beween he daa values which are calculaed by old parameers and new parameers separaely. Algorihm o Coherence o Semanic Caching Managemen Inserion Algorihm o PR-ree: Aer execuing a LDQ, he server insers he predicae o he LDQ ino he PR-ree, in order o reduce he workload o he server, we only inser he LDA predicae, which limis he recangle scope R in wo dimensions geographic plane. (I1) Compue he se o hashing secions covered by recangle R and le i be S; (I2) For each hashing secion, modiy is s i S query requency and he las ime o being queried; (I3) For each recangle O i o lea node, which is overlapped by R, modiy he query requency and is las ime o being queried o he lea node; (I4) I R is covered by union o O i, R will no be insered ino he PR-ree, and he server will reurn he resul o he query and will aach he code n_covered o indicae ha he predicae o he LDQ is no insered ino he PR-ree bu can be cached by he clien; (I5) Compue he µ and q o R. I µ >1/L or q <min_q, R will no be insered ino he PR-ree, and he server will reurn he resul o he query and will aach he code n_discarded o indicae ha he resul o he query can no be cached by he clien; The parameer L is he lengh o broadcasing window o he server, and min_q is he hreshold deining he query requency o a recangle secion composed o some hashing secions; (I6) Inser R ino he PR-ree, and reurn he code n_cached o indicae ha he resul o he query can be cached in he clien. Algorihm o Consrucion o HPIR Queue: Aer an updae operaion is execued, he server will

3 J. Compuer Sci., 1 (3): , 25 judge which daa iems have been eeced and consruc he predicae invalid repor o noiy he cliens who have cached hese iems o updae is cache. Le he recangle o he updae operaion be R. no in he se E. E is he se o record id o S i ; (C1) Updae he µ values o hashing secions and lea nodes covered by R; (C2) I updae operaion is a PU, ind he lea node which covers he poin o PU. I i is ound, hen consruc a new HPIR and inser i ino he HPIR queue; (C3) I he operaion is a RU, ind he lea node which is overlapped by R. I ind, hen consruc a new HPIR and inser i ino he HPIR queue. Algorihm o Coherence Managemen o Semanic Caching a he Clien: When he clien receives he resul rom he server, i checks he reurn code aached o he resul o decide wheher o inser he predicae o he query ino he HPCD. I he reurn code is no n_discard he clien will inser he predicae ino he HPCD and cache he resul o he query. The mos imporan issue o semanic caching managemen is he coherence o semanic cache. Algorihm o Updae o PCD (1) Lisen o he HPIR broadcasing and download he HPIRs, which corresponding o he local HPCD; (2) Le S i be a HPCD iem, and UO i be an updae operaion whose scope o LDAs is overlapped by ha o S i ; I UO i is a PU BEGIN I he id o he record PU updaed is already in he cache, hen updae he record locally; Else i all values o aribues updaed by his PU saisy he predicae o he PCD, hen inser an iem ino he updae queue UQ; END; Else BEGIN Le he recangle inersecion o S i and UO i speciied by he values o LDAs be A, and A is no empy. Le he inersecion o predicae speciied by he values o NLDAs o S i and UO i be B. I B is no empy Begin Updae all daa records locally, which saisy he predicae A and B; Le all he records whose values o NLDAs saisy he predicae: (NLDA (RU)\B) and A, be denoed by se C, in which he records are no in he S i. I UO i updaes all he aribues in NLDAs o S i and he modiied values o NLDAs o a record in C saisy he predicae o S i, hen Begin Inser a query ino he UQ, he predicae o which is: ((NLDA (RU)\B ) and A) and he record id is 353 TS-Cache Coherence Managemen Algorihm Noaion: Clien-Side: Lisen o he wireless channel o receive IR in ime during connecion ime; W h ile (n ew d aa rec e ive d ) { } δ = x x i ( δ > δ ) N o al + + ; i ( N o a l > N ) } { C om pue he new param eers o daa m odel; o r (a ll n e ig h b o u r h o s s o M S ) c o m p u e W i ; n eig h b o u rs o M S W s = W i / W i ; 1 A ssign each neighbour hos he ask o broadcas he T S -IR W s * W im es ; IR I (reconneced rom disconnecion mode) Ge IRs rom server which overlap i now; I (IRs received are relaed wih is TS-Cache) Choose he newes IR and updae he parameers o he model; Else I (imesamp o local TS-Cache is older han he hreshold predeined) Iinvalidae local TS-Cache; Perormance Analysis and Simulaion Resuls: We evaluae he eeciveness o our mehod in comparison wih he approach proposed in [1] which is called PIR by us. A irs, we inroduce he main parameers o simulaion model. Number o cliens 2 Daabase size 2 records Broadcas inerval 1 minues Ho records 6 records Ho daa access prob.8 1. The Mean Number o PIR Broadcased: From Fig. 1, we can see ha he number o PIR grows as he updae number increases. However, he growing rend is dieren beween he PIR algorihm and our algorihm. The PIR mehod will consruc a PIR whenever a record is updaed, no maer wheher he updaed record is cached by cliens or no. However, in our mehod, he server can deermine wheher o consruc a new IR according o he PR-ree. On he oher hand, i he updaed records are no ho daa, he probabiliy o being cached by cliens is low. In our algorihm, he server does no manage he predicae o cold daa, so many updaed cold daa will no be broadcased. As a resul, he growing rend o he PIR number o our algorihm develops more

4 slowly han ha o PIR algorihm. J. Compuer Sci., 1 (3): , 25 Mean number o PIR Fig. 1: Mean Updae Number Per Inerval PIR HPIR CONCLUSION In his paper, we propose some semanic cache mode and managemen algorihms which are based on PR-ree and Ts-Cache mehod. Simulaion resuls show ha our algorihm could save considerable bandwidh compared o he previously proposed algorihms. In uure research, we will exend our algorihm o deal wih he problem o ransacion processing wih semanic cache and we will exend our algorihm by using TS-Cache o deal wih he problem o query opimize. REFERENCES Mean number o downloaded records Number o Broadcasing Fig. 2: Mean Updae Number Per Inerval Fig. 3: Updaed Ho Daa PIR HPIR AD 2. Cos o Bandwidh or Downloading he New daa: The clien will download some new daa via requess o he server in order o make coherence o he cache, so some communicaion bandwidh will be used o do his. The Figure 2 shows he comparison beween algorihm PIR and our algorihm as or he number o records which have been downloaded. 3. Mean Communicaion Cos o Server: From Fig. 3 above we can ind ha in our TS mehod he number o broadcas daa is much smaller han ha o AD. The reason is ha he server in AD mehod mus broadcas ho daa which are updaed. Bu in TS mehod, only he daa whose error bound exceeds he hreshold will be broadcas o cliens. TS Qun Ren, Margare H. Dunham: Using semanic caching o manage locaion dependen daa in mobile compuing. MOBICOM 2: Seydim, MH.Dunham,V Kumar:Locaion Dependen Query Processing.MobeDe21 USA S. Dar, e al, "Semanic Daa Caching and Replacemen", Proc. VLDB Con AM.Keller,Julie Basu :A predicae-based caching scheme or clien-server daabase archiecures.vldb Journal(1996)5: Q Ren,MH.Dunham:Using Clusering or Eecive Managemen o a Semanic Cache in Mobile Compuing.MobiDe1999 WA USA, Guohong Cao: A Scalable Low-Laency Cache Invalidaion Sraegy or Mobile Environmens.ACM MOBICOM2 MA USA D. Barbara and T.Imielinkai, Sleepers and workaholics: Caching sraegies or mobile environmens, ACM SIGMOD,pages 1-12, T.Imielinksi, S.Viswanahan, and B. Badrinah, Energy Ecien Indexing on Air, IEEE Transacions on Knowledge and Daa Engineering, 9(3): , May/June G. Forman and J. Zahorjan, The Challenges o Mobile Compuing, IEEE Compuer, 27(6), April YD Chung e al: Predicae-based Cache Managemen or Coninuous Parial Mach Queries in Mobile Daabases. KAIST CS Technical Repor CS/TR P. Godrey and J. Grys. Semanic query caching in heerogeneous daabases. In Proceedings o KRDB a VLDB, pages , Ahens, Greece, Augus K.C.K.Lee, H.V.Leong, and A. Si. Semanic query caching in a mobile environmen. Mobile Compuing and Communicaions Review, 3(2):28-36, April Disribued Caching and Broadcas in a Wireless Mobile Compuing Environmen 14. J. Jing, A. Elmagarmid, A. Helal, and R. Alonso, Bi-Sequences: An adapive Cache Invalidaion Mehod in Mobile Clien/Server Environmens, Mobile Neworks and applicaions, pages , Yin-Huei Loh e al: A Hybrid Mehod or Concurren Updaes on Disconneced Daabases in Mobile Compuing Environmens. SAC (2) 2:

5 J. Compuer Sci., 1 (3): ,